Asian-Pacific Countries Comparison
load("./data/wine150_tidy")
wine150_tidy %>%
select(country, points_avg_country) %>%
filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>%
mutate(country = fct_reorder(country, desc(points_avg_country))) %>%
unique() %>%
mutate(text_label = str_c("Country: ", country, "\nAverage Points: ", points_avg_country)) %>%
plot_ly(
x = ~country, y = ~points_avg_country, color = ~factor(country), text = ~text_label,
type = "bar", colors = "viridis") %>%
layout(
xaxis = list(title = "Asian-Pacific Countries"),
yaxis = list(title = "Average Wine Points", range = (c(80,88))),
title = "Average Wine Points of Asian-Pacific Countries")
Top 20 Asian-Pacific Wineries
load("./data/wine150_tidy")
wine150_tidy %>%
select(points, country, winery, variety, points_avg_variety, points_avg_winery) %>%
filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>%
mutate(winery = fct_reorder(winery, desc(points_avg_winery))) %>%
filter(as.numeric(winery) <= 20) %>%
arrange(winery) %>%
plot_ly(
x = ~winery, y = ~points, color = ~factor(winery),
type = "box", colors = "viridis") %>%
layout(
xaxis = list(title = "Asian-Pacific Wineries"),
yaxis = list(title = "Wine Points"),
title = "Top 20 Asian-Pacific Wineries: Highest Professional Recognition")
Bottom 20 Asian-Pacific Wineries
load("./data/wine150_tidy")
wine150_tidy %>%
select(points, country, winery, variety, points_avg_variety, points_avg_winery) %>%
filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>%
mutate(winery = fct_reorder(winery, points_avg_winery)) %>%
filter(as.numeric(winery) <= 20) %>%
arrange(winery) %>%
plot_ly(
x = ~winery, y = ~points, color = ~factor(winery),
type = "box", colors = "viridis") %>%
layout(
xaxis = list(title = "Asian-Pacific Wineries"),
yaxis = list(title = "Wine Points"),
title = "Bottom 20 Asian-Pacific Wineries: Lowest Professional Recognition")
Top 10 Grapes for Asian-Pacific Wines
load("./data/wine150_tidy")
wine150_tidy %>%
select(points, country, winery, variety, points_med_variety, points_med_winery) %>%
filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>%
mutate(variety = fct_reorder(variety, desc(points_med_variety))) %>%
filter(as.numeric(variety) <= 10) %>%
arrange(variety) %>%
plot_ly(
x = ~variety, y = ~points, color = ~factor(variety),
type = "violin", colors = "viridis") %>%
layout(
xaxis = list(title = "Grapes for Asian-Pacific Wines"),
yaxis = list(title = "Wine Points"),
title = "Most Favorable 10 Grapes for Asian-Pacific Wines: Highest Professional Recognition")
Bottom 10 Grapes for Asian-Pacific Wines
load("./data/wine150_tidy")
wine150_tidy %>%
select(points, country, winery, variety, points_med_variety, points_med_winery) %>%
filter(country %in% c("Australia", "China", "Georgia", "India", "Israel", "Japan", "Lebanon", "New Zealand", "South Korea", "Turkey")) %>%
mutate(variety = fct_reorder(variety, points_med_variety)) %>%
filter(as.numeric(variety) <= 10) %>%
arrange(variety) %>%
plot_ly(
x = ~variety, y = ~points, color = ~factor(variety),
type = "violin", colors = "viridis") %>%
layout(
xaxis = list(title = "Grapes for Asian-Pacific Wines"),
yaxis = list(title = "Wine Points"),
title = "Least Favorable 10 Grapes for Asian-Pacific Wines: Lowest Professional Recognition")